LEE- Kontrol ve Otomasyon Mühendisliği Lisansüstü Programı
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Çıkarma tarihi ile LEE- Kontrol ve Otomasyon Mühendisliği Lisansüstü Programı'a göz atma
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ÖgeMulti-agent coverage control with adaptation to performance variations and imprecise localization( 2020) Turanlı, Mert ; Temeltaş, Hakan ; 637482 ; Kontrol ve Otomasyon Mühendisliği Ana Bilim DalıIn this thesis, an adaptive collaboration approach for a multi-agent system consisting of nonholonomic wheeled mobile robots is proposed. The positions of the agents are not known precisely but their locations are known to be within uncertainty circles. For the collaboration among the robots, the workspace partitioning algorithm is chosen as Guaranteed Power Voronoi Diagram (GPVD or GPD) which not only takes the localization uncertainty into account but also is capable of changing the regions of the generator points with respect to corresponding weight parameters. Also, the assumption is that the actuation capabilities of the robots are different from each other. The agents do not know those parameters related to their actuation performances beforehand. The contribution of the thesis is that the performance parameters of the agents are learned online by the proposed adaptive estimator algorithm and Hopfield Neural Network (HNN) estimator under localization uncertainty. The proposed algorithm is based on the coverage control which performs collaboration among the robots by assigning the regions from the workspace according to their actuation performances automatically. The definition of the actuation performances is different capabilities of the agents. The examples of strong actuation performances may include powerful motors and favorable terrain while wheel slip and weak motors can be counted as examples for the weak actuator performances. The proposed multi-agent collaborative coverage algorithm learns the performance parameters of the robots by using two approaches proposed in the thesis. The first approach is based on an adaptive estimator with a non-holonomic estimation model. The second method uses an HNN estimator. The theoretical proof, analysis and verification of the aforementioned methods are given in the related sections. After estimating the performance parameters, the weights are calculated using a neighbor based weight estimation algorithm. The weight variables are utilized in the GPD algorithm so that the workspace is partitioned according to the performance parameters of the agents in a guaranteed sense. At the end, the agents take regions from the workspace according to their actuation performances and achieve the optimal collaborative coverage so that the agents with strong actuators take larger regions from the environment than the agents with poor actuators. Thus, the collaborative coverage algorithm enables the robots to deploy themselves to an optimal configuration which minimizes the total coverage cost by taking imprecise localization into account. Moreover, a multi-agent coverage collaboration method with an energy-efficient optimal coverage control law and Hopfield networks is proposed in the related section. By using the algorithm a trade-off between coverage time and energy consumption among agents can be done. Meanwhile, the collaboration is achieved according to the actuation performances of the agents. The theoretical results are verified with MATLAB and ROS/Gazebo simulations and experiments that show the efficiency of the algorithm. The ROS implementation of the algorithm is explained. The experimental results are given in the related section.
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ÖgeActive slam with informative path planning for heterogeneous robot teams(Fen Bilimleri Enstitüsü, 2020) Akay, Mehmet Caner ; Temeltaş, Hakan ; İnsansız Hava Aracı'nı (İHA'yı) ve İnsansız Kara Aracı'nı (İKA'yı) bünyesinde bulunduran heterojen yapılı robot takımları, günümüzde gözetleme, takip, keşif, vb. farklı görevlerde kullanılmaktadır. Çevrenin haritalanmasını gerektiren keşif görevlerinde, heterojen robot takımlarının ortamı daha iyi anlayabilmesi adına, ortak bir haritaya ihtiyaç duyulmaktadır. Bu doğrultuda özel yaklaşımlarla, Lidar Odometre ve Haritalama (LOH) ile zorlayıcı yapıların bulunduğu ortamda, araçların kooperatif bir şekilde benzerlik metriklerini kullanarak ortak harita çıkarması sağlanmaktadır. Bunun yanı sıra, sınırları belirli bir alanın, heterojen robot takımları ile keşfini sağlamak adına sürekli olarak toplanan bilgiyi arttırıcı kontrolcü tasarımı kullanılmaktadır. Farklı tipte hareket denklemlerine ya da dinamik modellere ve/veya farklı sensör yapılarına sahip robotlardan oluşan robot takımlara heterojen yapılı robot takımları denmektedir. Diğer taraftan robot takımlarının eş zamanlı konumlama ve haritalama problemi ile bu takımdaki robotların yol planlamalarının eş zamanlı gerçeklemesi ise Aktif eş zamanlı konumlama ve haritalama (EZKH) problemi olarak adlandırılmaktadır. Buradaki eş zamanlı gerçeklemedeki amaç otonom robot araçları için planlanan yolların aynı zamanda EZKH'deki belirsizliği de minimize edecek şekilde gerçekleştirilmesidir. Diğer bir deyişle otonom robot araçları için bilgilendirici yol planlarının oluşturulmasıdır. Bu çalışmanın temel amacı heterojen yapılı robot grupları için bilgilendirici yol planlamaya dayalı bir Aktif-EZKH sistemi tasarlamaktır. Robot takımlarının farklı dinamik ve sensörlere sahip olması diğer bir deyişle heterojen yapıda olmaları, bu robot takımlarına avantajlar getirmektedir. Örneğin; hava robotları hızlı hareket edebilir, kara robotları daha ağır faydalı yükler taşıyabilir ve hedef nokta ile doğrudan etkileşime girebilirler. Karma bir araçlı bir yapı içerisinde yer alan İHA ile İKA oluşan bir robot grubu keşif, arama veya güvenlik amaçlı sınırları belirlene bir bölge içinde iş birliği yaparak ortam içindeki görevlerini insandan bağımsız bir şekilde otonom olarak gerçekleyebilir. Burada İHA ve İKA'ların birbirleri ile yer istasyonu aracılığı ile veri paylaşımında olduğu varsayılmaktadır. Komşuluk alanları içerisinde haberleşme ile harita paylaşımı ya da araç durum vektörü paylaşımı yapabilen robot birimleri kooperatif robotlar olarak gösterilmektedir. Bu çalışmada dış ortam sensörü olarak 360° ortam taraması yapabilen ve saniyede 300.000 adet noktanın mesafesini ölçebilen 3B LIDAR sistemi kullanılmıştır. Yüksek çözünürlüklü ölçüm avantajının yanı sıra bu kadar büyük miktardaki veriden optimum miktarda ve hızlı bir şekilde anlamlı veri üretip bunları robot konumlama, planlama ve koordinasyonunda kullanım da ayrı bir zorluk ortaya koymaktadır. Temel olarak, hareketli olan bir araçtan elde edilen nokta bulutunun coğrafik olarak yerleştirilmesi gerekmektedir. Bu işlem sadece Lidar sensörü kullanılarak da; farklı sensörlerin verilerinin ortak bir şekilde kullanılması aracılığıyla da yapılabilir. SadeceLidar ile toplanmış verilerin işlenerek nokta bulutunun coğrafik olarak yerleştirilmesi ve gözlem sırasında sensörün hareketinin elde edilmesi, bu çalışmada LOH ile sağlanmaktadır. Bu sayede; GPS ve IMU olmaksızın EZKH yapılabilmektedir. Buna ek olarak, sensörlere binen gürültülerden dolayı oluşabilecek kaymalar ve yanlış veri elde edilmesi engellenebilmektedir. Buna karşılık, GPS, enkoder ve IMU verileri ile Lidar verileri birleştirilerek Genişletilmiş Kalman Filtresi (GKF) konumlaması da sağlanabilmektedir. Burda sensör verilerinin olasılıksal yaklaşımlarla işlenmesi ile robotun konumu elde edilmektedir ve bu konum ile Lidar verilerinin coğrafik yerleştirme yapılması sonucunda da belirli bir orijine sabitlenmiş nokta bulutu çıktısı alınmaktadır. Sonrasında da bu nokta bulutu ile istenilen yöntem ile elde edilen odometre ve nokta bulutu verisi farklı haritalama yöntemleri kullanılarak ayarlanabilir özel görsel çıktılar sağlanabilmektedir. Bunlardan biri, sekizli ağaç yapıları kullanılarak elde edilen OctoMap olmaktadır. OctoMap yöntemi, tez çalışmasında kullanılmasının temel sebepleri olan, çözünürlük ayarlaması, doluluk olasılığı üst ve alt sınırları belirlenmesi ve 3B olarak sağlanabilmesi açısından faydalı bir araç olmaktadır. Bu yöntem ile, ortamın uyarlanabilir şekilde, ortamın 3B haritasının çıkarılması sağlanmaktadır. Lidar sensörlerinin havadan alınan nokta bulutları ile karadan alınan nokta bulutları farklı geometrik özellikler taşımaktadır. Ancak, hava ve kara Lidar görüntülemesinin birbirlerini tamamlaması bakımından oldukça büyük avantajları da mevcuttur. Hava aracı ve kara aracı tarafından yapılan ve birilerinin göremedikleri bölgelerin görüntülenebilmesi sağlanılmaktadır. Bu avantajı kullanabilmek adına farklı açılardan lokal olarak görüntülenen ortamın ortak bir haritada birleştirilmesi gerekmektedir. Harita birleştirme adımını gerçekleştirmek adına her iki robotun elde ettiği verilerden ortak olanını belirlemek gerekmektedir. Kuş bakışı veya yatay olması fark etmeksizin bir nesnenin yere göre yüksekliği; hem havadan hem karadan yapılan gözlemlerde sensörlerin görüş açısı sınırları içerisinde aynı olacaktır. Bu doğrultuda, yükseklik verileri üzerinden benzerlik metrikleri kullanılarak haritaların birleştirilmesi sağlanabilmektedir. Bu tez çalışmasında, İHA ve İKA tarafından elde edilen nokta bulutu ızgara haritasına benzer bir yapıda olan yükselti haritaları kullanılmıştır. Izgaralar ile bölünmüş hücrelerdeki en yüksek noktanın verisinin kullanılması ile 2.5D harita elde edilmesi sayesinde yükselti haritaları oluşturulmaktadır. Benzerlik metrikleri aracılığıyla ise bu haritadaki yükseklik bilgilerinin birbirine oturmasını sağlayacak konum ve yönelim farkı belirlenmektedir. Çalışmanın sonraki aşamalarında entropi teorisi kullanılması sebebiyle entropi temelli benzerlik metrikleri ile harita birleştirme yapılmıştır. Yedi farklı tipteki entropi metriği ile yapılan benzerlik karşılaştırması sonucunda "Jensen Divergence" entropi tanımının en az hata ile haritalar arasında dönme ve öteleme farkının belirlenmesini sağladığı, deneyler ile doğrulanmıştır. Ayrıca; haritanın dikey eksende katmanlara ayrılması ve bu katmanlar üzerinden yapılan yükseklik benzerlikleri hesaplaması ile optimum konum ve yönelim ( veya dönme ve öteleme) farklarının belirlenmesinin; katmanlara ayırma metodunun kullanılmasına göre daha avantajlı olduğu da gösterilmiştir. Her bir otonom araç "Harita Birleştirme" süreci sonrasında bu harita Aktif-EZKH süreci için kullanılarak hem harita bilgileri daha hassas hale getirilir hem de robotun gitmesi gereken yeni konumu tespit edilmiş olur. Yol planlaması, görevin etkin bir şekilde icrası için gerekli olan kritik adımlardan biridir. Enerji tüketim, elde edilen sonucun gerçekleşme süresi ve kalitesi uygulamanın ana kriterleridir. Bu nedenle, yol planlama algoritmaları etkin sistemler oluşturmak üzere kullanılmaktadır. Yol planlama algoritmaları farklı türde olabilir ama özelliklehedef işaretleme ve bilgi maksimizasyonuna dayalı yöntemler diğer yol planlama yöntemlerine göre belirgin üstün özelliklere sahip olanlarıdır. Hedef odaklı yol planlama algoritmalarında, birimlerin belirli bir hedefe ulaşabilmesi adına oluşturduğu kontrol eylemleri bulunmaktadır. Bilgi maksimizasyonu yaklaşımı; ortam, nesnenin diğer nesneler veya bir hedef hakkında daha fazla bilgi almak için bir doğrultu boyunca hareket etmesi olarak tarif edilebilir. Burada bağıl entropi teorisi, bilgi maksimizasyonu yaklaşımı olarak sunulmuştur. İlaveten, bağıl entropi, karşılıklı bilgi ile çevresel durum entropisiyle arasındaki farktır. Bağıl entropi kullanılarak, bilgi metrik olarak ifade edilebilmektedir. Çevresel durumlar ile gözlemler ile elde edilen durumlar arasındaki bağıl entropi üzerinden yaratılan amaç fonksiyonunun optimal çözümü sonucunda elde edilen hedef nokta, o bölgedeki bilginin belirlenen kriterlere göre istenilen seviyeye çekilmesini sağlamaktadır. Bu, EZKH ile etkileşimli çalışan yol planlaması temelli bir optimal kontrol yöntemidir. Bu yöntem çerçevesinde Bilgi Teorisinden faydalanılarak belirsizlik terimleri ile entropi terimleri arasında ilişki kuran bir Karşılıklı Bilgi terimi tanımlanır. Kulback-Liebler Mesafesi olarak da tanımlanan bu Karşılık Bilgi terimi maksimum değerine ulaştığında belirsizleri temsil eden entropi terimleri de minimize olurlar. Bu sebeple Karşılık Bilgi terimine dayalı bir amaç fonksiyonu oluşturularak bu fonksiyonu maksimize yapacak robot konum ve hareket vektörleri optimal kontrol yaklaşımı ile elde edilir. Bu elde edilen terimler heterojen robot takımında yer alan otonom robotlara uygulanarak onların hareketleri planlanmış olur. Amaç fonksiyonunu Lyapunov kararlı yapan bu noktalar ise bir hacimsel bölgenin merkezidir ve bu hacimsel bölgedeki bilgiyi maksimize etmek üzere belirlenmiştir. Bu noktaya ulaşmak için, robotlar belirlenen kurallar çerçevesinde hareket etmektedir. Bu kurallar ise İHA veya İKA'nın hedef noktaya hareketinin seçimi ve hedef noktaya ulaşım için engellerden kaçınmayı içermektedir. Bu yöntemin; özellikle farklı boyutlarda nokta bulutu ölçümü yapabilen hava be kara araçlı robot takımındaki uygulamaları literatürde mevcut değildir. Bu teorik çalışmaları ön plana alan çalışmaların çıktılarının özellikle arama-kurtarma, keşif ve güvenlik gibi robot takımı uygulamaları için büyük önem taşıyacağı değerlendirilmektedir. Önerilen yöntemde, ortamdan yapılan ölçümler ile araç hareketlerinde oluşabilecek belirsizliklerini etkilerini en aza indiren kara ve hava robotlarından oluşan heterojen yapılı robot takımlarının keşif amaçlı yol planlama algoritmalarının geliştirilmesi ve performanslarının test edilmesi hedeflenmiştir. Aynı zamanda, bu görevleri icra edebilmek adına belirli harita birleştirmenin de gerçekleştirilmesi gerekmektedir. Öncelikle; harita birleştirilmesi yönteminin doğrulanması adına üniversite kampüsünde belirli bir bölgede kara aracı olarak Clearpath Husky A200, hava aracı olarak ise DJI Matrice 600Pro ve bu araçlar üzerinde bulunan Lidar sensörü kullanılmıştır. Sonuç olarak; teorik çalışmalarda verilen benzerlik metriklerinden en optimum olanı deneyler aracılığıyla belirlenmiştir. Sonrasında; bilgilendirici yol planlama yönteminin doğrulanması amacıyla Robot İşletim Sistemi ("ROS") ve Gazebo temelli, karmaşık ancak günlük yaşantıda karşılaşılabilinen bir simülasyon ortamı kurulmuştur. Bu simülasyon ortamında altı farklı durum yaratılarak heterojen robot takımları için bilgilendirici yol planlamalı Aktif EZKH gösterilmiş ve parametre ayarlamaları ile uygulamaya göre değiştirilebilir bir yapı sağlanmıştır. ; 650277 ; Kontrol ve Otomasyon Mühendisliği Ana Bilim DalıRecently, heterogeneous teams consisting of unmanned ground vehicles and unmanned aerial vehicles are being used for different types of missions such as surveillance, tracking, and exploration, etc. Exploration missions with heterogeneous robot teams should acquire a common map for understanding the surroundings better. The unique approach presented in this dissertation with cooperative use of agents provides a well-detailed observation over the environment where challenging details and complex structures are involved. Also, the presented method is suitable for real-time applications and autonomous path planning for exploration. Lidar Odometry and Mapping with various similarity metrics such as Shannon Entropy, Kullback-Liebler Divergence, Jeffrey Divergence, K Divergence, Topsoe Divergence, Jensen-Shannon Divergence and Jensen Divergence are used to construct a common height map of the environment. Furthermore, the given layering method that provides more accuracy and a better understanding of the common map. All of the given similarity metrics are compared, and the advantage of utilizing the layering method is shown. The best similarity metric for constructing a heterogeneous robot team common map of the experimental area was obtained by using the Jensen Divergence similarity metric and layering method. Moreover, Extended Kalman Filter localization and OctoMap techniques are utilized to create an adaptive simultaneous localization and mapping infrastructure for informative path planning. Optimal parameter tuning for the specified simulation environment provides adjustable memory allocation and exploration performance, such as; duration, collected information and effort. The information seeking controller obtained with the use of relative entropy ensures exploration of the given area to minimize the uncertainty between observed states and environmental states. Robots move to the volumetric spaces' center under given rules and collect measurements by proprioceptive and exteroceptive sensors. With the use of heterogeneous robot teams, the measurements collected by the Lidar provide an advantage in perceiving complex details that can not be done by homogeneous robot teams. Constructing common map part of the theoretical approaches in this thesis are experimentally validated. In addition, the complete demonstration of this dissertation is done with six different cases by simulation studies. The theoretical background of active simultaneous localization and mapping with informative path planning for heterogeneous robot teams are validated, and the advantages of this study are remarked.
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ÖgeAnalysis and design of general type-2 fuzzy logic controllers(Fen Bilimleri Enstitüsü, 2020) Sakallı, Ahmet ; Kumbasar, Tufan ; 656903 ; Kontrol ve Otomasyon Mühendisliği Bilim DalıThis thesis presents new interpretations on the design parameters of the general type-2 fuzzy logic controllers by investigating their internal structures, proposes novel systematic design approaches for the general type-2 fuzzy logic controllers based on comprehensive and comparative analyses, and validates theoretical findings as well as proposed tuning methods via simulation and real-time experiments. The fuzzy systems have been successfully realized in a wide variety of engineering areas such as controls, image processing, data processing, decision making, estimation, modeling, and robotics. The fuzzy logic systems provide complex mappings from inputs to outputs, and this benefit usually results in better performances in comparison to non-fuzzy counterparts. Due to this, the fuzzy logic controllers have been applied to numerous challenging control problems for decades. Nowadays, more attention has been given to a new research direction of the fuzzy sets and systems, the general type-2 fuzzy logic controllers, which is the main motivation of this thesis. The internal structures of a class of Takagi-Sugeno-Kang type fuzzy logic controllers are first examined in detail. In this context, three fuzzy logic controller types (type-1, interval type-2, and general type 2) and two kinds of controller configurations (single-input and double-input) are considered. The baseline controllers, i.e. type-1 and interval type-2 fuzzy logic controllers, are presented in the preliminaries section. The fuzzy sets, fuzzy relations, fuzzy rules, fuzzy operators, and PID forms of these fuzzy logic controllers are explained in detail. The design assumptions and design parameters are given, also the most common design approaches are listed. Afterward, the general type-2 fuzzy sets and the general type-2 fuzzy logic controllers are presented. The general type-2 fuzzy logic controllers are described with α-plane associated horizontal slices because the α-plane representation provides useful advantages on the handling of the secondary membership function of the general type-2 fuzzy sets and the calculation of the general type-2 fuzzy logic controller output. It is shown that the α-plane based general type-2 fuzzy logic controller output calculation is accomplished through the well-known interval type-2 fuzzy logic computations. The secondary membership functions are further detailed in terms of their mathematical definitions and design options. The structure analysis on the general type-2 fuzzy sets shows the interactions between non-fuzzy, type-1 fuzzy, interval type-2 fuzzy, and general type-2 fuzzy sets happen in the secondary membership function. It is shown that the general type-2 fuzzy logic controller can easily transform into interval type-2 fuzzy, or type-1 fuzzy counterparts based on the secondary membership function definitions. As an outcome of this structural analysis, a new representation of the trapezoid secondary membership function is proposed based on a novel parameterization of the parameters that form the trapezoid shape. It is shown that the parameterized trapezoid secondary membership function is capable to construct trapezoid, triangle, interval, and singleton shapes so that the general type-2 fuzzy logic controllers are further capable to transform into interval type-2 fuzzy, or type-1 fuzzy counterparts. It is also shown that the proposed parameterization of the trapezoid secondary membership functions allows designing the control curves/surfaces of the general type-2 fuzzy logic controllers with a single tuning parameter. Moreover, the structural design suggestions are presented not only to construct fuzzy controllers in a straightforward manner but also to ease the design of the controllers with few design parameters. The design parameters of the general type-2 fuzzy logic controllers are grouped as the shape and the sensitivity design parameters with respect to their effects on the accuracy and the shape of the resulting fuzzy mapping. Accordingly, the tuning parameter of the secondary membership functions and the total number of α-planes are interpreted and as the sensitivity and shape design parameters, respectively. The shape analyses of the general type-2 fuzzy logic controllers show the effects of the proposed shape design parameter on the control curves/surfaces. In this context, the resulting fuzzy mappings of single input and double input general type-2 fuzzy logic controller structures are compared for various design settings of the shape design parameter. The comparative analyses provide interpretable and practical explanations on the potential advances of the shape design parameter. Based on the shape analyses, novel design approaches are proposed to tune the shape design parameter in a systematic way. In this context, it is suggested constructing the general type-2 fuzzy logic controllers over their type-1 and interval type-2 baselines and tuning them via the shape design parameter by providing a tunable tradeoff between robustness and performance. Therefore, it is aimed to combine benefits of baseline type-1 (relatively more aggressive control curves/surfaces better performance measures) and interval type 2 (relatively smoother control curves/surfaces, better robustness measures) fuzzy logic controllers. To enhance the control performance, two scheduling mechanisms are also proposed for online-tuning of the shape design parameter with respect to the steady-state operating points as well as transient-state dynamics. The sensitivity analyses of the general type-2 fuzzy logic controllers show the effects of the proposed sensitivity design parameter on the accuracy of the control curves/ surfaces. In this context, the resulting fuzzy mappings of single input and double input general type-2 fuzzy logic controller structures are also compared for various design settings of the sensitivity design parameter. The comparative sensitivity analyses show interpretable and practical explanations of the sensitivity design parameter in terms of calculation accuracy and computation burden. Therefore, it is suggested tuning the sensitivity design parameter by considering the limitations of hardware components such as resolution and processing speed. To accomplish the design in accordance with a tradeoff between sensitivity and computational time, a novel iterative algorithm is proposed to tune the sensitivity design parameter. The simulation and real-time experimental control studies validate the proposed design recommendations, systematic design approaches, and tuning methods for the general type-2 fuzzy logic controllers on benchmark control systems. In these control studies, the general type-2 fuzzy logic controllers are designed based on the proposed design methods. In order to show the performance improvements on the control systems, the general type-2 fuzzy logic controllers (tuned either online or offline) are compared with type-1 fuzzy and interval type-2 fuzzy counterparts. The performance measures clearly show that the online-tuned general type-2 fuzzy logic controllers outperform all general type-2, interval type-2, and type-1 counterparts on account of the proposed scheduling mechanisms over the proposed systematic design rules. The results also show that the systematic design of the general type-2 fuzzy logic controllers is simply accomplished by following the proposed tuning steps of the shape and sensitivity design parameters.
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ÖgeDiscrete-time adaptive control of port controlled hamiltonian systems(Fen Bilimleri Enstitüsü, 2021) Alkrunz, Mohammed ; Yalçın, Yaprak ; 657354 ; Kontrol ve Otomasyon Mühendisliği Ana Bilim DalıIn control theory, the design of the adaptive controllers in the discrete-time setting for nonlinear systems has been an interesting area of research. The adaptive controller deals with the problem of finding an appropriate and efficient control structure with an adaptation mechanism to preserve stability and an acceptable closed-loop performance in the existence of a considerable amount of uncertainties or time-varying parameters. It is well known that nonlinear systems are sensitive to disturbances, unknown noises, and parameter perturbations. For these kinds of perturbed systems, adaptive control theory is a powerful tool to establish compensation procedures in an effective way that automatically updates the controller to improve the performance of the controlled systems. This thesis study considers adaptive control of an important class of nonlinear systems so-called Port-controlled Hamiltonian systems (PCH) with uncertainty in their energy function and proposes adaptive discrete-time controllers with novel construction of parameter estimators for the multiplicative uncertainty case, the linearly parametrized case, and the nonlinearly parameterized case. The proposed method adopts the Interconnection and Damping Assignment Passivity-based control (IDA-PBC) as the control design method and the Immersion and Invariance (I&I) for parameter(s) estimation. Therefore, the two approaches, namely, the IDA-PBC and I&I techniques, are combined in a discrete-time framework such that all the trajectories of the closed-loop system are bounded, and system states successfully converge to the stable desired equilibrium points, namely the minimum of the desired energy function. As mentioned previously, the Immersion and Invariance (I&I) approach is considered to develop an automatic tuning mechanism for the adaptive IDA-PBC controller. To comply with I&I conditions, for each case, the estimation error dynamic is defined such that it includes a free design function of the system states, and then the parameter estimator is constructed by establishing a parameter update rule and by presenting a novel function for the mentioned free design function such that Lyapunov stability of the estimator error dynamics is ensured. This novel design function includes some parameters, that can vary in a determined range, to provide the ability to assign desired dynamics to the estimator error system. By replacing the uncertain terms with the values obtained by the I&I estimator, the closed-loop system is immersed in the desired closed-loop system which would be obtained with the IDA-PBC controller with true parameters. In the multiplicative uncertainty case, and as an initial formulation of this study, the uncertainties in energy function appear as multiplicative uncertainties to the gradient of the Hamiltonian function. Unlike the other two formulation cases, no specific perturbation is considered in the system parameters and instead, a general multiplicative uncertainty is presented to the gradient of the Hamiltonian function and thus the adaptive IDA-PBC controller is constructed considering this multiplicative uncertainty formulation. The I&I based estimator is designed by selecting an update rule and presenting a general structure for the free design function such that the estimator error dynamics are Lyapunov asymptotically stable. The proposed general structure includes a free parameter that enables to assign different desired dynamics to the estimator. By including the proposed estimator in the constructed adaptive IDA-PBC controller, the local asymptotic stability of the obtained closed-loop system is shown in a sufficiently large set. One underactuated Hamiltonian system example is considered. In the linear parameterized case, the uncertainties of system parameters appear linearly in the energy function and thus the uncertain system dynamics are formulated such that these uncertainties appear in linearly parameterized form in the gradient of the Hamiltonian function. By considering this formulation of the linear parameterization of the uncertain system parameters, the adaptive IDA-PBC controller is constructed. Since PCH is linearly parameterized in the proposed formulation, the gradient of the Hamiltonian function could be factorized in two terms such as one of the terms becomes a matrix that includes all the known terms of system states and system parameters while the other term is a vector of unknown parameters. The mentioned matrix can be a full column rank or not. In the case where this matrix is full rank, the Lyapunov asymptotic stability of the estimator is proved while the Lyapunov stability of the estimator is shown for the case when it is not full rank. It is also shown that, for the case of having not full rank matrix, the term representing the effect of uncertainties in the closed-loop system dynamics obtained with the IDA-PBC controller that uses the estimated parameters approaches to zero. Furthermore, the Lyapunov asymptotic stability of the obtained closed-loop system is shown in a sufficiently large local set either the matrix is full rank or not. For the I&I based estimator design, a general structure for the free design function that includes some free parameters is presented that makes the estimator error dynamics Lyapunov stable where these free parameters are in a determined specific range. So that, by selecting different values for these free parameters in the determined range, different desired dynamics can be assigned to the estimation of each unknown parameter. Three linearly parameterized examples are considered; two fully actuated systems (One has a formulation with a full rank matrix while the other has a formulation with a not full rank matrix), and one underactuated system. In the nonlinear parametrized case, the parameter uncertainties that appear nonlinearly in the energy function are considered. A proper formulation for uncertain system dynamics is presented such that the uncertainties appear in non-linearly parameterized form in the gradient of the Hamiltonian function and the adaptive IDA-PBC controller is constructed considering this formulation. The conditions on the Lyapunov asymptotic stability of the estimator dynamics are derived. Namely, it is proved that if these conditions are satisfied, the estimator error dynamics become asymptotically stable. Assuming these conditions are satisfied, local asymptotic stability of the closed-loop system, which is obtained when the proposed estimator is used with the adaptive IDA-PBC controller, in a sufficiently large set is proved. For the I&I based estimator design, a structure for the free design function of the estimator is proposed including some other free design functions to satisfy these conditions however it is seen that it is not easy to give general suggestions for these last free functions. It is concluded that for each example, a special selection of these functions is needed. Two nonlinearly parameterized examples are considered and proper selections of the free design functions in the proposed structure is performed. One of the example is a fully actuated mechanical system while the other one is under-actuated. The simulation results for each of the previously mentioned systems illustrated the effectiveness of the proposed adaptive controller in comparison to the non-adaptive controller for the same test conditions. The estimator successfully estimates the uncertain parameters and the adaptive IDA-PBC controller that utilizing these parameters stabilizes the closed-loop system and preserves the performance of the stable desired Hamiltonian systems.
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ÖgeA stable, energy and time efficient biped locomotion(Lisansüstü Eğitim Enstitüsü, 2021) Yılmaz, Sabri ; Gökaşan, Metin ; 725780 ; Kontrol ve Otomasyon MühendisliğiThis thesis presents two different walking strategies for biped robots while ensuring energy efficiency. The first strategy is a closed-loop walking controller based on the most used 3-Dimensional (3D) Linear Inverted Pendulum Model (LIPM) which is used to calculate the Zero Moment Point (ZMP) approximately. The closed-loop Proportional Integral (PI) controller's coefficients are searched by the Genetic Algorithm (GA), which is developed to overcome the 3D LIPM's dynamical insufficiency. Because of its ease of modeling, the key concept is to continue to use the 3D LIPM with a closed-loop controller. For this purpose, the biped is modeled using the 3D LIPM, which is one of the most well-known modeling approaches for humanoid robots due to its ease of use and quick computations during trajectory planning. Model Predictive Control (MPC) is applied to the 3D LIPM once the simple model is obtained to search the reference trajectories for the biped while meeting the ZMP criteria. The second strategy is to express the ZMP in a detailed model instead of an approximate model. For this purpose, the biped is modeled with the conventional robot modeling methods and the detailed expression of the ZMP is obtained. Then the problem is redefined as a Nonlinear MPC problem. The highly complicated biped model is implemented in Matlab with the use of CasADi Library which is a symbolic library and used on large symbolic solutions. The optimal control problem is solved with the Interior Point Optimizer (IPOPT), which is an optimization solver for large equations. With the solution of the optimal control problem, reference trajectories are found for the biped while satisfying the ZMP criteria. Both strategies suggested in this thesis are studied and implemented on a biped robot which means the robot has no upper body elements. The main idea is that if the dynamic flaws are suppressed without any upper body elements, this study will open a way to work on more modular robots. After obtaining two different walking strategies, the energy-efficient trajectory for the swing leg is searched to have longer working durations on the field. The Big Bang Big Crunch with Local Search (BBBC-LS) global optimization algorithm is used for energy efficiency. With the newly defined trajectory there became nearly 10% energy consumption reduction compared to the sinusoidal trajectory. To implement the algorithms to the real biped, a new communication library is written to meet the desired communication speed. But with the increased speed in communication, there became random packet losses on the feedback from the motors. These packet losses are examined and it is observed that these random packet losses may make the system unstable, so to suppress the effects of packet losses the problem is redefined as a time delay problem. With the redefinition of the problem, the well-known Smith Predictor method is used to overcome the packet losses and from the results, it can be seen that with this redefinition the instability risk because of the packet losses has disappeared. In a short summary, a two-legged robot has been modeled using conventional methods in the literature. First, the dynamic defects of the simple model are eliminated with a conventional controller. Secondly, a more detailed dynamic model is obtained. Walking planning is done with both methods and comparisons are made with the method commonly used in the literature. The success of the proposed methods has been demonstrated in both simulations and experimental results. With the two methods proposed in this thesis, the oscillation problem encountered by one of the most widely used walking models in the literature has been resolved. After obtaining stable walking, energy optimization is studied so that the robot could work longer in the outdoor environment and trajectory improvement is made to reduce energy consumption during the robot's movement. Finally, a faster communication library is written to apply the designed algorithms to the real system and to solve the problems caused by communication speeds, the problem is redefined with a different approach and the traditional method, Smith Predictor, is used. Packet losses that are random thanks to the communication interfaces prepared for the mechanism; become predictable and the effects of packet losses are eliminated with Smith Predictor. Finally, all these control methods are applied to the system and used in experimental studies.
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ÖgeDoğrusal olmayan sistemler için model öngörülü kontrol yöntemine ters optimal kontrol yapısının katılması(Lisansüstü Eğitim Enstitüsü, 2021-08-02) Ulusoy, Lütfi ; Güzelkaya, Müjde ; 504122103 ; Kontrol ve Otomasyon MühendisliğiOptimal kontrol probleminin amacı, bazı kontrol ve durum kısıtlamalarını sağlayacak ve bir başarım kriterini optimize edecek şekilde bir kontrol giriş fonksiyonu veya kontrol kuralı elde etmektir. Buna rağmen, optimal kontrol kuralı, kısıtsız ve doğrusal durumlarda bile oldukça kolay ve analitik olarak bulunamaz. Optimal kontrol kuralının çözümünün Hamilton-Jacobi-Bellman (HJB) denklemini çözmeyi gerektirdiği iyi bilinen bir gerçektir ki bu son derece zordur. Dahası, doğrusal olmayan sistemlerin çoğu için analitik bir HJB çözümü mevcut değildir. Sistem doğrusal olduğunda ve başarım kriteri ikinci dereceden olduğunda, HJB, belirli durumlarda analitik olarak çözülmesi zor olabilen bir Riccati denklemi olarak ortaya çıkar. Bu zorlukların üstesinden gelmek amacıyla önceden belirlenmiş bir sonlu ufuk için mevcut sistem durumunu, başlangıç durumu olarak atayarak, sistem modeli yardımıyla optimal kontrol problemini tekrar tekrar ve ardışıl olarak çözmek düşünülmüştür. Bu stratejiyi kullanan kontrol yaklaşımları, Model Öngörülü Kontrol (MÖK) olarak adlandırılır. Bu yaklaşımda, sistemin gelecekteki davranışı, sistem modeli kullanılarak tahmin edilir ve kontrol işareti, anlık sistem durumlarına göre her kontrol ufku için tekrar tekrar yenilenir. Öte yandan, HJB problemini çözmek yerine bize farklı bir bakış açısı sağlayan bir başka yaklaşım ise Ters Optimal Kontrol (TOK) teorisidir. TOK, HJB denklemini çözmenin zahmetli görevinden kaçınarak, doğrusal olmayan optimal kontrol problemini çözmek için alternatif bir yaklaşımdır. Son yıllarda, birçok gerçek zamanlı uygulamada doğrusal olmayan optimal kontrol problemlerini çözmek için ters optimizasyon yaklaşımı giderek daha fazla kullanılmaktadır. Tezde, ilk olarak model öngörülü kontrol yaklaşımının optimal kontrol problemini ele alış biçimi anlatılmıştır. Önerilecek yöntem ile karşılaştırabilmek amacıyla, klasik model öngörülü yaklaşımlarından, doğrusal sistem modelini kullanan gradyant tabanlı MÖK ve doğrusal olmayan sistem modeli Runge-Kutta tabanlı MÖK (RKMÖK) yaklaşımları verilmiştir. Daha sonra ters optimal kontrol (TOK) yaklaşımları incelenmiş ve ayrık-zamanlı girişte-afin doğrusal olmayan sistemler için TOK problemini Kontrol Lyapunov Fonksiyonu (KLF) bulma problemine dönüştürerek çözen TOK yaklaşımı anlatılmıştır. TOK yaklaşımı için takip probleminde karşılaşılabilecek sorunlar üzerinde durulmuştur. Bu tezde ilk olarak, takip problemi sorunlarını çözebilmek amacıyla kontrol işareti ağırlık matrisinin her bir elemanı için sistem durum değişkenlerine bağlı bir sigmoid fonksiyon önerilmiştir. Önerilen yaklaşımın başarımını gösterebilmek için klasik TOK yaklaşımıyla karşılaştırma yapılmıştır. Bu tez çalışmasında, ayrıca girişte-afin doğrusal olmayan sistemler için MÖK ve TOK yaklaşımları birleştirilerek yeni bir optimal kontrol yöntemi önerilmektedir. Gerçek hayatta ve literatürde karşılaşılan doğrusal olmayan sistemlerin ve sistem modellerinin çoğu, bazı doğrusal olmayan azaltma yöntemleri ile girişte-afin biçime dönüştürülebilir. Önerilen yöntemin temel özelliği, her kayan ufuk ve sonuç olarak yeni bir başlangıç koşulu için çözülmesi gereken MÖK optimizasyon problemini TOK problemi olarak ele alıp, bu TOK problemini tekrar tekrar çözmesidir. Bu yaklaşımda, sistemin gelecekteki davranışının tahminini elde etmek için sistem modeli kullanılır ve önceden belirlenmiş bir kontrol ufku için TOK yönteminden elde edilen kontrol işareti sisteme uygulanır. TOK probleminin çözümü aşamasında, belirlenmesi gereken aday kontrol Lyapunov fonksiyon matrisinin parametreleri, evrimsel Büyük Patlama-Büyük Çöküş (BP-BÇ) optimizasyon arama algoritması kullanılarak çevrim içi bir şekilde tahmin edilir. Önerilen kontrol yapısında, MÖK yaklaşımında her kontrol ufku için uygun bir KLF matrisinin aranması ile optimal kontrol problemi çözülmektedir. Diğer bir bakış açısından ise, MÖK yapısı TOK problemine dahil edilerek TOK problemi, her kayan ufkun başlangıcındaki farklı başlangıç koşulları kullanılarak tekrar tekrar çözülmekte ve böylece, TOK için çevrim içi bir düzeltme mekanizması elde edilmektedir. Bu yaklaşım ve literatürdeki diğer yöntemler kullanılarak top ve çubuk kontrol sistemi üzerinde benzetim çalışmaları ve gerçek zamanlı uygulama yapılmıştır. Elde edilen sonuçlar bazı kontrol başarım ölçütlerine karşılaştırılmış ve önerilen yaklaşımın başarımı değerlendirilmiştir.
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ÖgeImproved fuzzy logic based edge detection method on clinical images(Graduate School, 2022-01-07) Çelen, Murat Mert ; Üstoğlu, İlker ; 504191145 ; Control and Automation EngineeringSignal processing is the main field combining electrical engineering and mathematics, used to analyze digital and analog signals. Signal processing deals with the storage, compression, filtering and other processing of signals. These signals can be sound signals, image signals, and other signals. Nowadays images are essential thing for many area. Images can be used in space researches, military applications, marine workings, automotive industry, environment, agriculture and medical science. The area where the signal type is processed is that the input is an image, and the output is also an image, which is called image processing. Image Processing is one of the main research area in the disciplines of computer science and engineering. Image processing is a methods which performs operations on an image, on account of get an information from image. The progress of image processing are improved by the help of: the development of technology, the development of discrete theory, the demand for a pretty wide range of applications. It can be divided into digital and analog image processing. Image processing for analog images is used for hard copies of photos. Digital image processing uses computers to process digital images. Image processing has various kind of application such as sharpening, blurring, contrast adjustment, and edge detection etc. Edge detection is helpful for applications in the fields such as fingerprint matching, medical diagnosis, license plate detection, biomedical imaging, pattern recognition and machine vision. Edge detection technique makes the high intensity valued pixels visible. Edge detection is a compelling assignment. When edge detection must be applied to noisy images, it becomes more difficult. The idea of fuzzy logic helps to get rid of this problem with expert knowledge. The concept of fuzzy logic was first proposed in the 1960s by Professor Lütfi Aliasker Zade in Berkeley. Lütfi Aliasker Zade is committed to translating natural language into computer language, but it is not easy to translate into computer language terms 0 and 1. Zade proposed a shape of polyvalent logic within which the truth valuation of variables is also any real number between 0 and 1 whereas classical logic theory is utilizing with values false or true. Fuzzy logic can be summarized as predicated on the observation that individuals make decisions supported vague and non-numerical information. Fuzzy models are numerical implies of speaking to dubiousness and uncertain data. These models have the inclination of deciphering and controlling information and information that are non-certain. Additionally, it's conceivable to characterize linguistic variables like brief, exceptionally brief, long, or exceptionally long with fuzzy logic. Lütfi Zade's proposed theory fuzzy logic has been applied to various fields such as robotics, artificial intelligence, modeling and controlling system which is nonlinear or digital image processing. These fields used type-1 fuzzy logic until Prof. Lütfi A. Zade presented type-2 fuzzy logic in 1975. Fuzzy logic's type-2 theory was improved for uncertainties and non-linearity due on type-1 fuzzy rules, it shows fuzzy logic frameworks on type-2 are more fruitful than fuzzy logic frameworks on type-1 to unravel vulnerabilities. Be that as it may, working with fuzzy logic frameworks on type-2 are distant more advanced than working with fuzzy logic frameworks on type-1. In this thesis we will talk about a type-1 edge detection with fuzzy logic implementation for medical brain images, with the assistance of digital image, and digital image processing. This thesis gives you the performance comparison of widely used edge detection methods and improved edge detection with fuzzy logic method with interpreting digital images with the help of image enhancement and restoration and performing operations on images such as blurring, contrast adjustment. Different sources of digital images will be tested and results for each source will be provided.
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ÖgeController design methodologies for fractional order system models(Graduate School, 2022-01-25) Yumuk, Erhan ; Güzelkaya, Müjde ; 504152101 ; Control and Automation EngineeringFractional order calculation deals with cases where the derivative and integral order is non-integer. Although the notion of fractional order was introduced at the end of the 17th century, this concept in engineering was employed after the first quarter of the 19th century. Its first application to control engineering areas was made after the second quarter of the 20th century. Since fractional calculus is a generalized version of integer order calculus, it provides great flexibility in system modeling and controller design. In other words, fractional calculus offers three different combinations in terms of the controller and system types: Fractional order control for integer order system, Fractional order control for fractional order system, and Integer order control for fractional order system. In this respect, fractional calculus is an excellent tool to describe a control system compared to integer order calculus. Besides the flexibility, the notion brings more complexity to system modeling and controller tuning. Therefore, many studies over the last half-century have been trying to overcome these difficulties. Numerous real-time systems have nonlinear characteristics and high-order system dynamics. In literature, simple integer-order models, i.e. the first and second order with or without time delay, are used to represent system dynamics.
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ÖgeRobotic fish for monitoring water pollution(Graduate School, 2022-02-01) Ansari, Mohammed Javed ; Doğan, Mustafa ; 504161131 ; Control and Automation EngineeringThe vast majority of the earth's surface is covered by water. Some parts of the ocean are so deep that even Mount Everest would be lost into them as if it never existed. Water bodies, irrespective of fresh or salty, big or small, all of them host some of the most unique ecosystems. Mankind is known to have set its sails into the oceans for time immemorial now. But it has only been possible in recent years that they have dived inside by the means of HOVs, ROVs, and AUVs. And still, most of it remains unexplored. Every living thing from a unicellular amoeba to Antarctic blue whales including every single plant needs water to survive. Otherwise, the earth would be as barren as any other planet known so far. The key to fact that life exists on the earth is water. But unfortunately, the amount of garbage of all kinds being dumped into the sources of water pollutes them and in a long run adversely affects and endangers the living things on planet earth. As our very existence depends on water, it's indispensable to monitor and take essential steps to preserve the water quality accordingly. Not only does water avail a sustainable condition for the terrestrial inhabitants, but also is a habitat to a huge number of species within. One of the most well-known species among these aquatic animals is fish. In this work, a brief study of types of fishes along with their structural definition is carried out to determine how they propel and swim in the water with their fin and then eventually use the discoveries to biomimetically design and implement a robotic fish capable of exploring water and taking certain readings with inbuilt sensors. The thus obtained readings can be used to monitor water. The robotic fish here tries moving in the water replicating the motion behaviors of a fish. This study consists of 5 different parts. Chapter 1 provides a brief introduction of the whole idea and the classification of fish according to their swimming behavior. Fishes swim in the water using their fins. They use their fins to produce a propulsive force that pushes them forward. Depending upon which part of the fish and how it pulsates fishes can be categorized into different classes. These classifications help study fishes better. A detailed categorization on the basis of various grounds is further discussed in this chapter. A common approach to classify fishes is based on the modes of propulsion that a fish applies while swimming i.e. whether undulatory or oscillatory methods of generating propulsive forces. These two categories of fish swimming modes are BCF (body and/or caudal fin) locomotion, and MPF (median and/or paired fin) locomotion. A thing common in these modes of propulsion is that the caudal fins play the most important role in producing the propulsive force generation. In this study, a "Carangiform & Fusiform" model has been adapted for replication. The first chapter also gives a brief description of "Biomimetics" along with some of its popular applications in various fields. Later in this chapter, the overall implementation of this work has been mentioned. Chapter 2 discusses works of a similar kind. It also comprises the methods used in other similar works. The caudal fin drive mechanism can be of single, multiple, or compliant type. It is already known that the caudal fin plays the most important role in swimming and maneuvering. And the stiffness of the joint that connects the caudal fin to the body of the fish is equally important for efficient swimming. Unlike other similar works, Turfi uses a single joint method with a soft caudal fin. The outer cover of Turfi was designed using SolidWorks. The 3D model was later printed using a 3D printer. The outer body of Turfi was divided into 2 halves while designing. The first half enclosed all the electronics (including the SD card module, battery, sensors, processor, and driver circuits) and the motors. The pectoral fins are controlled using micro servo motors that help Turfi in maneuvering and the caudal fin is driven using a dc motor attached to a reduction mechanism. The other half of Turfi is the caudal tail and its mechanism that creates the oscillatory motion in the caudal fin by the means of the dc motor. The caudal fin drive mechanism converts the rotary motion of the dc motor to oscillatory motion. The front enclosure part was 3D printed using Polylactic Acid (PLA) because of its stiffness. The posterior i.e., the caudal fin was made using Thermoplastic Polyurethane (TPU). TPU is best known for flexibility. Making the caudal fin with TPU gives the caudal fin a soft and flexible structure thus making the propulsion wavy and smooth. The ESP32 used as the processor is also embedded with a WiFi module. ESP32 is programmed to create an Async WiFi server. The asynchronous server allows Turfi to take the readings and store them on an SD card even when offline. And when connected can deliver all the data collected at once. This helps Turfi to navigate and collect data irrespective of its connection to the base station. Turfi while navigating underwater takes the sensor readings and stores them into an SD card. After the completion of navigation, Turfi resurfaces and connects with the base station using WiFi and sends all the readings made during the navigation. Turfi later. These readings can be accessed using an IP provided by ESP32. These details are discussed in Chapter 3. As this study progressed further it was seen that Turfi can be programmed in various ways to accomplish different tasks. In the 4th Chapter, the results of two different tests are included. In the first test, Turfi was programmed to take readings at a certain depth (i.e., 20cm). A PID controller using PID Library by Brett Beauregard was used to track the depth based on the readings from the depth sensor. The second test was similar to the first one except that Turfi was instructed to take left and right turns. 5th Chapter concludes this work by describing the complexity of multi-fin locomotion underwater. It also briefly explains how Turfi can be developed in order to accomplish further. Upgrades such as a camera to record underwater, sensors to measure pH, oxygen level, salinity, etc. can be attached to Turfi. These sensors can help Turfi monitor underwater in a more detailed way. An exit mechanism is also proposed in this section. The exit mechanism would help Turfi resurface in case the battery is below a certain level or once the navigation is complete. Once atop, the whereabouts of Turfi can be known using GPS. There have been works of similar nature done priorly. But most of them tend to focus on a descriptive analysis of the swimming behavior of a fish and then replicating it. In this work, the scope has been slightly widened by adding the sensors to make required readings. One major hindrance similar to the ones of previous works i.e., limitation to wirelessly communicate well is experienced while working on this project as well. Thus, a different approach is applied in this study. In this approach, Turfi is instructed to follow a certain navigation route. While navigating underwater, Turfi also stores the sensor readings on an SD card. These data can be retrieved wirelessly from Turfi over WiFi. Thus, obtained data can be used for further processing.
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ÖgeZaman gecikmeli sistemler için kural kaydırma tabanlı bulanık mantık kontrolör tasarımı(Lisansüstü Eğitim Enstitüsü, 2022-02-01) Ateşova, Müge ; Güzelkaya, Müjde ; 504171136 ; Kontrol ve Otomasyon Mühendisliği ; Control and Automation EngineeringZaman gecikmeli sistemlerin kontrolü pratikte en çok karşılaşılan kontrol problemlerinden biridir. Literatürde bu kontrol problemi üzerine pek çok çalışma ve uygulama bulunmaktadır. Zaman gecikmeli sistemlerde karşılaşılan sorunların temeli sistemden gözlenen bilginin geçmişe ait olmasına dayanmaktadır. Bu durumun kontrolör tarafından algılanması mümkün olmadığı için başarısız sonuçlara neden olabilmektedir. Probleme temel bir bakış açısıyla yaklaşmak gerekirse, kontrol sistemine giren bilginin geçmiş zamana ait olması durumunda bunun algılanıp duruma göre bir ayarlama yapılmasının soruna çözüm olması beklenir. Bulanık mantık kontrol yapıları üzerine yapılan çalışmalardan bazıları kontrolörün katsayılarını değiştirmeden kural tabanının kaydırılması ile zaman gecikmesinin sistem yanıtı üzerindeki olumsuz etkilerinin azaltılabileceğini göstermiştir. Sistem modelleri elde edilirken sahip olabilecekleri zaman gecikmesinin dikkate alınmış olması gerekir. Ancak zaman gecikmesinin gerçekte modelde bulunan değerinden farklı olduğu durumlar ile karşılaşılabilir. Bu durumda kontrol sisteminden beklenilen başarım elde edilemez. Bu çalışmada, ölü zamanın modelde bulunan değerinden daha az veya daha fazla olduğu durumlar için modele göre belirlenmiş bulanık mantık PID kontrolörünün kural tablosu değiştirilmiştir. Bu işlem sırasında bulanık kontrolör kural tablosu satırları uygun miktar ve yönlerde kaydırılmıştır. Kural tablosunun düzenlenmesinin etkisini görebilmek adına çalışmalar boyunca her bir sistem modeli için bulanık mantık kontrol katsayıları genetik arama algoritması yardımıyla belirlenmiştir. Genetik arama algoritması için arama kriteri zaman ağırlıklı hata karelerinin toplamı (ITSE) olarak seçilmiştir. ITSE kriteri aynı zamanda sistemin farklı kural tabanları ile başarımını incelemek için de kullanılmıştır. Ayrıca, sistemdeki zaman gecikmesinin değişmesi durumuna kontrol yönteminin bu değişime bağlı olarak uygun kural tabanını kullanabilmesi için öz-ayarlamalı kural tabanı yöntemi önerilmiştir. Bu amaçla sistem modelinde var olan zaman gecikmesinin çeşitli değişimleri için uygun olan kural tabanları belirlenmiştir. Bu kural tabanları arasında, belirlenen zaman gecilmesine bağlı olarak geçiş yapabilen bir kontrol yapısı kurulmuştur. Öz ayarlamalı kontrol yapısı, kural tabanı kaydırılmamış bulanık mantık kontrol yöntemi ve zaman gecikmesi bilinen sistemler için belirlenmiş olan kural tabanı kaydırılmış bulanık mantık kontrol yöntemi ile karşılaştırılmıştır. Elde edilen ITSE değerleri tablolar halinde verilirken, sistem yanıtları grafik halinde gösterilmiştir. Tahmin edilebileceği gibi zaman gecikmesi bilinen sistemler için uygun kural tabanı kaydırması ile elde edilen kontrol sistemlerinin benzetim sonuçları öz-ayarlamalı kontrol yönteminin uygulandığı zaman gecikmesi bilinmeyen sistemlerin benzetim sonuçlarından belirlenen başarım kriterine göre daha başarılı olmuştur. Fakat, çizelge ve grafikler göstermektedir ki öz-ayarlamalı kontrol yöntemi ile kural tabanı kaydırılmamış bulanık mantık kontrol yöntemini kıyaslandığında öz-ayarlamalı kural tabanı yapısı daha başarılı olmuştur.
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Öge2-step indoor localization for "smart AGVs"(Graduate School, 2022-06-17) Yılmaz, Abdurrahman ; Temeltaş, Hakan ; 504142101 ; Control and Automation EngineeringWith the fourth industrial revolution, in other words, Industry 4.0 (I4.0), the transition from traditional mass production to personalized production started in factories. One of the components of the next-generation factories compatible with I4.0 is cyber-physical systems (CPSs). Smart manufacturing islands, smart warehouses, and smart material-handling vehicles are examples of CPSs. The material handling vehicles employed in today's factories, such as automated guided vehicles (AGVs), are not ready for use in smart factories, as the digital transformation has not been completed and the vehicles are not equipped with software to perform fully autonomous operations. In smart factories, it is aimed that the new generation AGVs will do all the planning themselves while performing a given task. Thus smart AGVs will be able to use the whole free space in the factory instead of being restricted to the routes reserved for them. With this development, it will be possible to increase flexibility and efficiency in production. There may be no physical difference between the traditional and smart AGVs, but thanks to the capabilities of the embedded software, smart AGVs will be able to operate autonomously. One challenging problem to be overcome for smart AGVs to effectively realize an assigned logistic task is localization. Although localization is an extensively studied topic for both indoor and outdoor environments, there are still open problems. Considering the logistics problem, the localization problem can be divided into three in the general sense. The first is global localization, which means determining where the smart AGV is in the environment at the time the vehicle wakes up. The second problem is position tracking, which means updating the pose information depending on the movements of the robot, while the instantaneous pose of the robot is known. The third and last problem is the kidnapped robot problem, which occurs when the robot is moved from one place to another without informing. Cases that reduce the reliability of the calculated pose, such as instantaneous skidding, slipping, and crashing an object, can also be addressed under this problem. The localization approach to be utilized in smart factories is supposed to overcome these three sub-problems. There are two main tasks in a logistic operation. The first is the docking stage, which covers the cases of taking a load to the smart AGV or dropping the load of the smart AGV. At this stage, the aim is to reach the target (destination) where the load will be taken or left with industrial standards. With I4.0, reaching the target with sub-centimeter precision has become a goal. Therefore, estimating the pose with high accuracy and precision is expected from the docking localization algorithm. The second is the delivery stage, which covers carrying the load to the destination in the fastest and safest way in the parts outside the docking region. It is not essential to follow the planned route exactly in this stage, so rather than the high accuracy of the localization approach, showing similar positioning performance in the entire operating field is more important. Within the scope of this thesis, different localization algorithms have been proposed for the delivery and docking stages. In addition, a probabilistic decision mechanism that determines the boundary between the delivery and docking stages is designed. A variant of the particle filter-based Monte Carlo Localization (MCL) approach, Self-Adaptive MCL (SA-MCL), is taken as the basis localization method for the delivery stage. The main reason for choosing SA-MCL is that it can solve all aforementioned sub-problems of localization. While performing the traditional SA-MCL global localization task, it uses energy maps and assumes that all range sensors are uniformly placed on the robot in energy map generation. However, this assumption is not valid for many real applications, such as AGVs with two-dimensional (2D) laser scanners front and rear. Moreover, three-dimensional (3D) sensing technology is developing day by day with the widespread use of autonomous vehicle technology. With the ellipse-based energy model proposed in this thesis, the energy map-generating part of the traditional SA-MCL has been updated to overcome both of these constraints. The pose estimation accuracy of the SA-MCL approach performs more or less the same across the entire environment, making it suitable for the delivery stage. However, since the pose estimation accuracy level is proportional to the grid dimensions of the occupancy map, it may not be possible to reach the expected sub-centimeter precision within the docking region in large areas such as factories. Therefore, it was decided to use a scan matching-based precise localization algorithm in the docking region, and for this purpose, the affine iterative closest point (ICP) algorithm was adapted to the localization problem. To make the developed method robust against factors such as noises, disturbances, and/or outliers, the correntropy criterion was utilized while constructing the cost function of affine ICP. As a result, an updated SA-MCL method with an ellipse-based energy model is proposed for the solution of global localization, position tracking, and kidnapped robot problems in the delivery stage. On the other hand, an affine ICP-based precise localization approach is presented for position tracking in the docking stage. However, the boundary between the delivery stage and the docking stage may not be clear. For example, limiting the docking stage to a zone very close to the target may require extra maneuvers to tolerate positioning errors during the delivery stage due to the physical constraints of smart AGVs. If a larger area is specified as a docking stage, it may not meet the expectations since the performance of the precise localization approach may decrease further away from the target. For this reason, there is a need for a switching mechanism that can be adapted specifically to the application and decides whether to switch from the delivery stage to the docking stage. Since the pose estimation performance of the SA-MCL-based localization approach is roughly similar on the entire map, the deciding factor in the transition to the docking stage is the performance of the precise localization method used in the docking stage. In the literature, it is emphasized that the amount of overlap between matched point sets is supposed to be above 50% for the scan-matching-based methods to yield successful results. Within the scope of the thesis, a correntropy-based similarity rate definition, which gives better results than the overlap ratio calculation methods in the literature, is presented and utilized as the decision parameter of the switching approach. To avoid instabilities, a gap is left according to Hysteresis curve behavior while switching from the delivery stage to the docking stage or vice versa. Within the scope of the thesis, the two-stage localization method developed for the next-generation AGVs to be used in smart factories has been experimentally tested on a differential drive mobile robot. First, the ellipse-based energy model addition to the SA-MCL method has been verified by field tests, and its superiority in global localization has been demonstrated. Then, the affine ICP-based localization method used in the docking stage has been tested over nine separate real-world scenarios and it has been shown that it is possible to compute pose with sub-centimeter precision and reach the target at industrial standards. In addition, an affine ICP method, which is not available in the literature, was proposed, and the point set matching performance was demonstrated over synthetic point sets. After validating its performance in point set registration, it was also used for precise localization. Finally, the whole system was tested together. The delivery was carried out with improved SA-MCL, and the switching point from delivery to the docking stage was determined by the decision mechanism. As seen through three different scenarios, it is possible to complete the localization tasks in the delivery and docking stages in the smart factories by using the proposed methods.
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ÖgeDeep reinforcement learning for partially observable markov decision processes(Graduate School, 2022-07-19) Haklıdır, Mehmet ; Temeltaş, Hakan ; 504102110 ; Control and Automation EngineeringDeep reinforcement learning has recently gained popularity owing to its many successful real-world applications in robotics and games. Conventional reinforcement learning faces a substantial challenge in developing effective algorithms for high-dimensional environments. The use of deep learning as a function approximator in reinforcement learning is a viable solution to overcome this challenge. Furthermore, in deep reinforcement learning, the environment is often thought to be fully observable, meaning that the agent can perceive the true state of the environment and so act appropriately in the current state. Most real-world problems are partially observable and the environmental models are unknown. Therefore, there is a significant need for reinforcement learning approaches to solve these problems, in which the agent perceives the state of the environment partially and noisily. Guided reinforcement learning methods solve this issue by providing additional state knowledge to reinforcement learning algorithms during the learning process, thereby allowing them to solve a partially observable Markov decision process (POMDP) more effectively. However, these guided approaches are relatively rare in the literature, and most existing approaches are model-based, which means that they require learning an appropriate model of the environment first. In this thesis, we present a novel model-free approach that combines the soft actor-critic method and supervised learning concept to solve real-world problems, formulating them as POMDPs. We evaluated our approach using modified partially observable MuJoCo tasks. In experiments performed on OpenAI Gym, an open-source simulation platform, our guided soft actor-critic approach outperformed other baseline algorithms, gaining 7∼20% more maximum average return on five partially observable tasks constructed based on continuous control problems and simulated in MuJoCo. To solve the autonomous driving problem, we focused on decision making under uncertainty, as a partially observable Markov decision process, using our guided soft actor-critic approach. A self-driving car was trained in a simulation environment, created using MATLAB/SIMULINK, for a scenario in which it encountered a pedestrian crossing the road. Experiments demonstrate that the agent exhibits desirable control behavior and performs close to the fully observable state under various uncertainty situations.
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ÖgeFunctional safety for heavy-duty transmissions(Graduate School, 2022-09-22) Bozdağ, Konuralp Tevfik ; Üstoğlu, İlker ; 504191117 ; Control and Automation EngineeringThe number of electrical and electronic equipment and software used in vehicles is increasing day by day. Apart from passive safety precautions for these hardware and software used, now active precautions are also taken. While the seat belt was a passive safety measure in the first years when vehicles became a necessity for the society, many software and hardware measures are now taken for the safety of the driver and passengers. Thanks to the autonomous transportation, the driver's place in transportation is decreasing, while his safety and security are gaining more and more importance. A system or piece of hardware must operate appropriately in accordance with the system's inputs in order for functional safety to be a component of the overall safety framework. To put it another way, functional safety refers to the capacity to recognize potentially dangerous circumstances and to trigger a protective or corrective device or mechanism to stop the development of hazardous events or to lessen their potential effects. The only means for the driver to act in an emergency while driving an automobile is to press the brake pedal. However, thanks to the software created thanks to functional safety, accidents can be prevented by intervening to the vehicle faster than the driver in an unexpected situation. Electrical, electronic, and programmable electronic everything is determined within the framework of certain rules and steps, functional safety analyzes and safety levels within the purpose of the IEC 61508 standard. Functional safety is included in the ISO 26262 standard group, being customized for the automotive sector. The ISO 26262 standard series describe how software and hardware for an automotive should be developed in certain road conditions and accident situations. In this thesis, the subject of functional safety will be examined in the automatic transmission system used in heavy vehicles. Today, due to globalization and the increase in consumer needs, logistics and transportation sectors gain more importance. Transportation is of great importance in these sectors and heavy vehicles have a large share in this sector. Trucks, trucks, etc., for both the safety of people and the transportation of products without any damage. It is important that vehicles are safe and secure. Among the working subjects of the automotive industry, the transmission software and designs of heavy-duty vehicles have an important value. The heavy-duty transmission to be analyzed is an automated manual transmission, with 16 forward and 4 reverse gears. Gear shifts are not only with synchromesh, but also by using 3-stage actuators, more combinations are created with less gears, and a lighter transmission is designed than expected. However, functional safety becomes more important in heavy-duty vehicles that have more hardware and software in terms of software and hardware. Because, in heavy-duty vehicles, the gearbox not only provides regular and desired torque transmission, but also fulfills different duties depending on the service type. Therefore, safety analyzes and created scenarios are investigated in more detail. In this research, firstly, the safety analysis of the heavy-duty vehicle was carried out according to the ISO 26262 standard group. In order to make a more detailed examination as the system where the safety analysis will be made, the system limits have been determined as automatic transmission and actuators. Then, the problems that may arise in the vehicle and transmission are considered and it is determined what kind of dangers may occur. Considering these hazards, hazard and risk analysis has been made for specific scenarios. What kind of safety goals should be taken against the hazards that may arise because of the hazard and risk analysis and how long it should take are defined in the functional safety concept. The analysis made was examined in detail and the safety requirements were established for the transmission software. The safety targets and requirements that emerged as a result of the safety analyzes were tested in the simulation environment. By means of model-based software, a dynamic model of the heavy-duty vehicle is created, and simple transmission algorithms are demonstrated. By creating virtual hazards and scenarios in Matlab & Simulink environment, vehicle models with and without functional safety software are compared.
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ÖgeTrajectory tracking control of a quadrotor with reinforcement learning(Graduate School, 2023-01-23) Çakmak, Eren ; Doğan, Mustafa ; 504181134 ; Control EngineeringDrone control algorithms are usually broken down into several steps. The innermost parts of a drone control algorithm are angle and angular velocity control loops. Whether it is fixed-wing or rotary-wing, these control loops conventionally consist of PID based controllers. Although a PID controller can control these loops successfully, it may not lead the outer loops to desired positions or velocities. An outer loop designed to manage these situations can be done with conventional controller loops. However, these kinds of controllers are heavily model-dependent and often require tuning. Motivated by this situation, the aim of the presented study is to show that reinforcement learning based algorithms can control a quadrotor drone without prior knowledge of the model. The most preferred model-free reinforcement algorithms in the literature are DDPG, TRPO, and PPO. The studies that use state-of-the-art reinforcement learning methods for quadcopter control are compared, and it is concluded that PPO is the best choice to begin with. An actor-critic neural network for PPO-clip, the most successful version of PPO, is built and trained on a custom Gym environment. The environment is a quadrotor model that covers fundamental dynamics. This study is composed of six chapters. In the first chapter, motivation of research and literature review are given. In the second chapter, the theoretical background to construct a quadrotor model is given, and a general picture of reinforcement learning and model-free algorithms is drawn. In the third chapter, a custom simulation environment using the features of Gym library is designed. Then, the neural network based controller is designed, in the fourth chapter. Next, the agent is trained in the custom environment, in the fifth chapter. The simulation results of hovering and trajectory tracking tests are given. In the last chapter, it is concluded that a model-free reinforcement learning-based neural network without any additional control loop can control a quadrotor, and possible future works for this study are discussed.
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ÖgeFuzzy logic based clutch torque curve detection algorithm for heavy duty vehicles(Graduate School, 2023-01-24) Cantürk, Ogün ; Üstoğlu, İlker ; 504191124 ; Control and Automation EngineeringIn this thesis, a fuzzy logic-based clutch torque curve learning algorithm is proposed as the second method to eliminate the mentioned disadvantages. The torque curve can be determined with this method without the necessity for any specific maneuver and activation conditions. Using a reference point on the curve, the fuzzy logic-based algorithm determines the position value corresponding to the reference point with respect to different clutch temperatures and the first torque transfer points. In this study, 581 Nm was chosen as the reference point. The fuzzy logic theory was introduced by L. A. Zadeh in 1965. Since then, it has been utilized in numerous fields, including the automotive, transportation, robotics, and chemical industries. The theory basically transforms the relationship between concepts into linguistic rules and permits expert opinions and experiences to be incorporated into system models. Fuzzy controllers consist of three main parts: fuzzifier, rule-based inference engine, and defuzzifier. Mamdani and Takagi-Sugeno type of fuzzy controllers are the most commonly used. MATLAB-Simulink was used for simulation studies. First of all, the conventional algorithm model was developed. The activation conditions, timer, and curve calculation functions used in the model are mentioned in detail. Secondly, two different fuzzy controllers, Takagi-Sugeno and Mamdani types, were designed. The purpose of designing different types of controllers is to compare the performances of the controllers for this problem. While designing the controllers, MATLAB's "Fuzzy Logic Designer" interface was utilized. In order to make a realistic comparison, the same input membership functions and rules are used in the controllers. The inputs of the controllers are selected as the clutch temperature and the first torque transfer point. Three membership functions are defined for each input: "low", "medium" and "high". The output of the controllers is the clutch position corresponding to the reference torque. As with the inputs, three different output membership functions are defined as "low," "medium," and "high" for both controllers. During the design of fuzzy controllers, the relationship between inputs and outputs was determined by analyzing data collected from multiple vehicles. After designing both controllers, a mechanism was created to choose between the conventional algorithm and the fuzzy-based algorithm. The decision mechanism basically compares the reference clutch position values obtained from the two strategies. If the difference between the calculated reference values exceeds a predetermined upper threshold, the error is detected, and the curve obtained from the fuzzy-based strategy becomes equal to the final output. If the difference between the calculated reference values is below a lower threshold, the error is deactivated, and the curve obtained from the conventional algorithm becomes equal to the final output. Thus, as the traditional algorithm will not be activated until the first launch maneuver, the error value will be high and the fuzzy-based strategy will be effective. So, the mechanism eliminates the feeling of poor performance on the first launch. Moreover, the output of the fuzzy controller will be continuously updated based on the change in clutch temperature and the first torque transfer point while driving. The fuzzy controller will be activated if an error is detected, preventing incorrect torque curve learning situations. For testing and validating the developed model, a two-step test procedure was created. First, launch maneuver data was collected for three different clutch temperature ranges: low (40-70°C), medium (70-90°C), and high (90-120°C) from a test vehicle with a 28-ton, construction truck variant. The relationship between traditional and fuzzy controller-based algorithms was examined by feeding the vehicle data to the generated MATLAB-Simulink model. This study was carried out separately for models using Takagi-Sugeno and Mamdani type fuzzy controllers. The obtained clutch torque curves were compared for 40, 70, and 100 °C clutch temperatures, one value from each temperature zone. In the second step of the test, the torque curves obtained from the conventional algorithm, Mamdani, and Takagi-Sugeno type fuzzy controllers for different clutch temperatures were validated by performing launch maneuvers on the same test vehicle. For each test, the maneuvers were repeated with the same gear, accelerator pedal, and road conditions. The verification was done by examining the difference between engine and clutch torque during the launch maneuver. A large difference between torque values indicates that the clutch is in the wrong position. For this reason, the difference between the torque values was defined as the error. Three different performance indexes ISE, ITSE and ITAE were used to compare the performance of the strategies analytically. Since the ITSE and ITAE indices are time-dependent, they evaluate launch maneuvers in terms of duration. The test results were analyzed in three sections as low, medium, and high. At low clutch temperatures, both Mamdani and Takagi-Sugeno fuzzy controllers outperform the conventional algorithm. Moreover, Mamdani provides better results according to ISE index, whereas Sugeno outperforms according to ITAE and ITSE indices at low clutch temperatures. The main reason for this is that when a Sugeno-type fuzzy controller is used, the launch times are reduced. For medium clutch temperatures, all three strategies were yielded similar results. As at low temperatures, Mamdani provides better results according to ISE index, whereas Sugeno outperforms according to ITAE index at medium clutch temperatures. According to the ITSE index, the performance of the two strategies is equal. For all three indices, the traditional algorithm has the lowest performance. However, there is no dramatic difference in the results of the three strategies. For high clutch temperatures, Sugeno has the worst performance according to all three indices. The main reason for this is that the Sugeno type fuzzy controller is much more sensitive to high clutch temperatures than the Mamdani type fuzzy controller. In addition, Mamdani type fuzzy controller has the best performance for all three indices. In general, it was observed that fuzzy controllers improved clutch torque curves. On the other hand, fuzzy controllers increased computational load and simulation times. Both types of fuzzy controllers have improved the performance of the first launch maneuvers. Sugeno type fuzzy controller is highly sensitive to changes in high clutch temperatures. Therefore, it showed poor performance at high temperatures. The Mamdani-type fuzzy controller, on the other hand, succeeded in all three test scenarios.
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ÖgeAsenkron motorun farklı kontrol yöntemleri ile hız kontrolü ve raylı sistemlere uygulanması(Lisansüstü Eğitim Enstitüsü, 2023-02-09) Çalıcıoğlu, Alp Eren ; Söylemez, Mehmet Turan ; 504181130 ; Kontrol ve Otomasyon MühendisligiHareketin olduğu tüm alanlarda motorlara da ihtiyaç vardır. Başta üretim, ulaşım, enerji gibi genel sektörler olmak üzere gündelik hayatımızda karşımıza çıkan küçük ev aletleri, beyaz eşyalar ve akla gelen çoğu alanda motorlar kullanılmaktadır. Artan dünya nüfusu ve modernizasyon ile birlikte motorlara olan ihtiyaç gün geçtikçe artmaktadır. Motor, kaba bir tabirle kullandığı enerjiyi hareket enerjisine çeviren makinelerdir. Kullanılan enerji katı yakıt, sıvı yakıt ve elektrik gibi çeşitli türlerde olabilir, bu yakıtları kullanan motorların farklı kullanım alanları vardır. Bu motorların birbirlerine göre avantajları ve dezavantajları bulunmaktadır. Çevre kirliliği günümüzde oldukça artmıştır ve gün geçtikçe de artmaya devam etmektedir, bu sebeple her alanda karşımıza çıkan ve çok yaygın şekilde kullanılan motorların çevre kirliliği açısından zararsız olması oldukça önemlidir. Elektrik motorları, yüksek verimleri, geniş tork ve hız karakteristikleri ve çevre dostu olmaları sebebiyle geniş bir kullanım alanı bulmaktadırlar. Farklı sınıflandırmalara göre çeşitli tipte elektrik motorları bulunmaktadır ve bu elektrik motorlarının farklı kullanım alanları, avantajları ve dezavantajları bulunmaktadır. Tez kapsamında simülasyonu yapılacak olan asenkron motorlar çok basit yapılıdırlar, bu sebeple oldukça ucuz, küçük boyutlu ve dayanıklı bir elektrik motoru türüdür. Benzer şekilde yapılarında fırça ve komütatör olmadığı için kıvılcım gibi güvenlik sorunları da oluşturmazlar ve bakım gereksinimleri yoktur veya çok kısıtlıdır. Asenkron motorlar, ulaşım ve üretim sektörü başta olmak üzere endüstride çok yaygındır. Asenkron motorlar, çalışma mantıkları gereği tek bir alternatif akım ile beslenirler. Statorun beslendiği bu akım yardımıyla rotorda akım endüklenir ve hareket oluşur, bu sebepten dolayı indüksiyon motoru ismiyle de isimlendirilirler. Basit çalışma mantığının getirdiği avantajlarının yanı sıra bazı dezavantajları da bulunmaktadır. Bunların başında DC motorlar gibi ayrı akımlar kullanılarak tork ve akı kontrolünün yapılamadığı gelmektedir, bu sebeple asenkron motorların kontrol yapıları ayrı akım ile sürülen elektrik motorlarına göre zordur. Ayrıca asenkron motorların doğrusal olmayan yapıları kontrol edilmelerini zorlaştırmaktadır. Asenkron motorların farklı kontrol yöntemleri mevcuttur, bunların başında skaler ve vektörel kontrol gelmektedir. Belirtilen iki yöntemin kullanım amaçları ve avantajları farklıdır. Bu çalışma kapsamında daha hassas kontrol sonuçları verebilen vektörel kontrol çalışılmıştır. Vektörel kontrol de kendi içerisinde doğrudan ve dolaylı vektörel kontrol olmak üzere ikiye ayrılmaktadır, çalışma kapsamında akı değerine ve pozisyonuna doğrudan ihtiyaç duyulmayan dolaylı vektörel kontrol yöntemi tercih edilmiştir. Vektörel kontrol ile birlikte asenkron motor bir DC motor gibi iki ayrı akım ile birlikte kontrol edilir ve bu sebeple yapılan kontrol işlemi nispeten basit bir hale getirilmiş olur. Ulaşım sektöründeki araç sayısı gün geçtikçe artmaktadır, bu sebeple ulaşım sektöründe kullanılan motorların çevreci ve yüksek verimli olması oldukça önemlidir. Demiryolu ulaşım araçları düşünüldüğünde yüksek çalışma saatleri, uzun süreli kullanım ömürleri ön plandadır, dolayısıyla itki sisteminin en önemli parçası olan motorun verimi çok önemlidir. Mıknatıslı elektrik motorları, verimin yüksek olduğu tüm alanlarda iyi bir alternatif olmaktadır, fakat yaşanan mıknatıs temini problemleri sebebiyle mıknatıslı elektrik motorlarındaki yaygın kullanım gün geçtikçe azalmaktadır. Metrolar, büyük şehirler için iyi bir ulaşım aracı alternatifidir, çünkü demiryollarını kullandıkları ve yer altından gittikleri için ek bir kara yolu şeridi işgal etmezler. Benzer sebeple insan yoğunluğunun fazla olduğu büyük şehirlerde, trafiksiz bir çözüm sundukları için kullanımları gün geçtikçe yaygınlaşmaktadır. Çalışma kapsamında MATLAB Simulink ortamında modellenen asenkron motor modeli bir metro aracında kullanılacak şekilde tasarlanmıştır. Metrolar çalışma prensipleri gereği genelde şehir içlerinde çalıştıkları için emniyet sebebiyle belirli bir hızın üstünde çalışmaları istenmez, ayrıca yolcu konforu ve emniyeti sebebiyle de belirli bir ivme üstüne çıkmaları engellenir. Bu limitler modelleme yapılırken dikkate alınmıştır, ayrıca asenkron motorun yapısı gereği oluşturulan modelin maksimum gerilim, maksimum tork ve maksimum güç üstüne çıkması engellenmiştir. Asenkron motor kontrolü düşünüldüğünde yukarıda bahsedilen emniyet ve konfor sebebiyle ivme kontrol altında tutulmalıdır, hız ve konum ise hassas bir şekilde kontrol edilmelidir, çünkü metrolardan belirlenen konumlarda ve çok küçük hata payı içerisinde durmaları beklenir. Ayrıca hız ve konum kontrolü için aşım istenen bir durum değildir. Bu performans kriterleri oluşturulan kontrol yapıları için göz önüne alınmıştır. Asenkron motorlar, diğer elektrik motorları gibi çalışırken ısınırlar, bu sebeple motor parametrelerinde ısınma sonucu değişimler oluşur. Ayrıca yukarıda bahsedildiği gibi asenkron motorların doğrusal olmayan yapılarından dolayı oluşturulan modelde belli kabuller yapılmıştır. Tüm bu model kaynaklı bilinmezlikler ve parametrik değişimlere ek olarak, metronun hareketini sürdürdüğü yoldan kaynaklı bilinmezlikler ve değişimler ve metro içerisine binen yolculardan dolayı oluşan toplam ağırlık değişimi yapılan kontrol yapısının dayanıklı olmasını gerektirir. Bu sebeple tasarlanan kontrol yapısının dayanıklı olması ve sistemi farklı koşullarda da başarılı bir şekilde kontrol edebilmesi de bir performans kriteri olarak göz önüne alınmıştır. Asenkron motor kontrolünde PID, PI-PD, bulanık kontrol, kayan kipli kontrol ve doğrusal olmayan dinamik tersleme yöntemleri kullanılmıştır. Bu kontrol yöntemleri asenkron motorun hız kontrolünü yapabilmek için tasarlanmıştır. Tasarımları yapılan kontrol yapıları istenen performans kriterlerine göre kıyaslanmıştır. Kullanılan kontrol yöntemlerinde tasarım yapılırken Osman Kaan Erol ve İbrahim Eksin tarafından ortaya atılan büyük patlama büyük çöküş optimizasyon yönteminden faydalanılmıştır. Çalışmada son olarak yapılan tasarımların karşılaştırmalı sonuçları yer almaktadır.
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ÖgeDifferential flatness-based fuzzy controller design for aggressive maneuvering of quadcopters(Graduate School, 2023-05-04) Güzay, Çağrı ; Kumbasar, Tufan ; 504142105 ; Control and Automation EngineeringThis study presents a new differential flatness-based single input fuzzy logic controller structure for aggressive maneuvering control alongside its real-world application on a nano quadcopter. We propose both type-1 and interval type-2 single input fuzzy logic controllers as the primary controllers in the flight control system, which are built on the concept of differential flatness. Today, quadcopters are used for a wide variety of applications and purposes such as aerial photography, search and rescue operations, surveying and mapping, inspection, agriculture, and emergency response. Quadcopters are getting more and more well-liked in the commercial and consumer markets as a result of the rising demand for their usage areas. Additionally, the dimensions of quadcopters have significantly changed along with the rapid development in contemporary technology. As a result, we can discuss quadcopter types such as mini, micro, or nano. Nano quadcopters, the smallest ones, are lightweight, more portable, and easier to operate and maneuver with high agility since they are constructed with small-scale rotors and frames.
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ÖgeAn online adjustment mechanism for membership functions of single input interval type-2 fuzzy PID controller(Lisansüstü Eğitim Enstitüsü, 2023-05-25) Aldreiei, Oqba ; Güzelkaya, Müjde ; 504191149 ; Control and Automation EngineeringThe characteristics of the footprint of uncertainty (FOU) in interval type-2 membership functions (IT2-MFs) are crucial for the performance and robustness of interval type-2 fuzzy controllers (IT2 FCs). However, existing IT2-FC designs mostly use fixed FOU structures. This study proposes an online adjustment mechanism for membership functions of single input interval type-2 fuzzy PID controller (SIT2-FPID) by adjusting the footprint of uncertainty (FOU) and the weights of the antecedent and consequent membership functions (MFs) respectively to achieve high performance and robustness. The proposed online adjustment mechanism consists of two main parts: relative rate observer (RRO) and adjustment mechanism which has two inputs "error" and "normalized acceleration (Rv)", whereas the "normalized acceleration" provides relative information about the fastness or slowness of the system response. Meta-rules for the modification of the output of online adjustment mechanism (γ) are derived according to the error value and the relative information on the fastness or slowness of the system response and by analyzing the transient phase of the unit step response of the closed-loop system. The output of online adjustment mechanism (γ) in the proposed online tuning method is used as a tuning variable for the footprint of uncertainty (FOU) of the antecedent interval type-2 membership functions and the weights of the consequent crisp membership functions. This provides a dynamic membership functions (MFs) structure, where the heights of the Lower MFs (LMFs) or Upper MFs (UMFs) of each IT2 fuzzy set and the weights of the crisp output are defined as functions of the output of online adjustment mechanism (γ). By doing so, the method accomplishes the task of an online adjustment of the FOU and the weights of the antecedent and consequent membership functions respectively. The single input interval type-2 fuzzy PID controller (SIT2-FPID) with the proposed membership function adjustment mechanism was compared with the conventional PID controller and single input interval type-2 fuzzy PID controller with fixed membership functions through simulations. Throughout the simulation studies seven different performance measures are considered, three of them classical transient system response criteria: settling time (Ts), overshoot (%OS), and rise time (Tr) and the other performance measures are considered as: Integral Absolute Error (IAE), Integral Square Error (ISE), Integral Time Squared Error (ITSE) and Integral Time Absolute Error (ITAE). In addition, a step input and output disturbances have been employed to observe the disturbance rejection performance of the proposed method. The proposed online adjustment mechanism for membership functions method is demonstrated to be effective in linear and non-linear systems through simulations, and to be efficient in compensation of input and output disturbances in a short period of time.